5 Pressing Global Issues AI is Solving
- Artificial Intelligence is a powerful tool capable of learning and executing various tasks
- Artificial Intelligence(AI) has the capacity to solve major global issues plaguing the planet
The use of Artificial Intelligence(AI) is increasing as technology progresses. Businesses are using AI to carry out mundane tasks with ease eliminating the human effort and the possibility of error that comes with it. The amount of data available to us is larger than ever. These data sets allow researchers to understand the trends a particular issue is following and generate a fundamental response to tackle that issue.
In the past few years, AI has set its feet firmly in our world. And while the sci-fi movies may lead us to believe that technological advancements in the domain of AI will doom the world, research shows that AI can help us solve a number of global issues that humans haven’t been able to solve yet.
In this article, I will explain how AI is solving 5 of the gravest global issues of times and helping us create a more sustainable and hopeful future.
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Table of Contents:
- The Great Plastic Tide
- AI to control Epidemics
- Efficient Energy Consumption with AI
- Prevent Global Food Crisis
- Accurate Medical Diagnoses
The Great Plastic Tide
Every year, the human population dumps around 8 million metric tonnes into the oceans. This figure will go up to 80 million metric tonnes a year by the year 2025 if we sit idle and watch. What we see is the minimal plastic waste that washes ashore on beaches but the huge pile-up of plastic waste that gets accumulated on the ocean beds is what remains unseen. This affects marine life as well as human lives.
Now, AI plays a critical role in curbing this global issue. Projects like Plastic Tide are determined to solve this problem using AI. They capture aerial photos using drones. Then photos are fed into an algorithm that tries to recognize what is there in each image and compares it with the labels of the image. Then, it calculates how accurate its guess is as compared to the actual contents and adjusts its techniques in order to improve its guesses.
The above-mentioned process is carries out multiple times in order to make the algorithm predictions better and enable it to improve the image sensing capability. The algorithm then differentiates between plastic trash and aquatic life. The ultimate goal is to create an open-source map of the worst polluted areas in the world. Once these places are located, the process to clean such areas can be initiated.
AI to Control Epidemics
In the time of an outbreak, the primary concern is to minimize the spread of the disease. Predictive analysis in epidemiology uses AI for this. A lot of historical data has to be fed to the AI for it to recognize patterns and trends, and then predict spreads using that data so that proper preventive measures can be adopted to minimize the spread.
The present times have made it easier to track the movement of people and hence analyze and predict the path that the disease follows. This can help focus the measures on preventing the spread and containing it to a particular region.
AI also helps in predicting the mutations and help develop vaccines with efficacy and safety.
Present usage of AI involves fighting COVID-19. The first case of COVID-19 was reported in Wuhan, China, and has spread to at least 100 countries since. Countries are relying heavily on AI to battle COVID-19. Bluedot, a Canadian startup, was the first to identify the risk and accurately predicted the global spread using its forecast models. Alibaba, the Chinese e-commerce conglomerate, developed a new AI system that detects corona virus with 96% accuracy.
Efficient Energy Consumption with AI
Humanity is using a massive amount of energy nowadays and this is increasing the need for clean energy. The main challenge is to supply the energy in accordance with the demand. The global electricity consumption rate saw a growth of rate of 3% per year over the time period of 2000-2018.
In the energy sector, AI can provide us with unconventional methods to save energy as well as generating clean energy. There is a great potential for AI in the future design of the energy system which will help us make the energy industry more efficient and robust.
Smart grid infrastructures distribute electricity and transfer data as well. The grids communicate energy consumption data and an AI evaluates for a more efficient supply. This incorporates the consumers intelligently into the system contributing to a green electricity grid. Smart home solutions and smart meters are available but attract fewer customers because the system is vulnerable to cyber-attacks. Increasing the security of these systems will surely result in an increase in the consumer base.
Google uses DeepMind, an AI system to autonomously manage cooling systems at its server farms. DeepMind constantly monitors the temperature of the servers and turns on the cooling systems when absolutely necessary. This has allowed Google to save about 40% of energy.
Also, Google and DeepMind are working together to apply AI and ML to renewable energy sources like wind power. Their AI is able to predict wind power output 36 hours prior to the actual generation. Hence, enabling them to make delivery commitments to the power grid a day in advance.
Prevent Global Food Crisis
With the increase in population by 1.1% or 83 million annually, the demand for food has surpassed the supply. This agflation affects the poor people across the world. Apart from poverty, other factors such as natural disasters are leading to a global food crisis. To combat this, organizations are looking towards AI for help. AI can efficiently predict food shortages and help in achieving food security, hence promoting the UN’s 2030 agenda for sustainable development.
Current methods for data analysis employ human experts which takes a lot of time. AI does it in much less time and that too at much lower costs. Again one of the obstacles in the way to achieve this is digitization. Many places in the poorer parts of the world are missing from the maps. Initiatives such as Missing Maps and OpenStreetMap aim to map these most vulnerable places in the underdeveloped or developing countries.
Climate change has substantially reduced harvests. With the help of weather forecast data, AI can predict disasters leading to a food crisis and in the process trigger actions that are required to prevent or manage these disasters. AI can analyze data from locating affected areas and then prompt the farmers to plant accordingly. Also, it can run permutations and combinations to come up with gene strains to produce “efficient” crops in order to increase the overall production.
The Famine Action Mechanism(FAM), is a joint initiative of the World Bank, United Nations, ICRC, and other global partners. It aims to enhance the capability to forecast areas that are at risk. In association with firms including Microsoft, Google, AWS, FAM will leverage the World Bank’s analytics and AI to provide early warnings. It will also link famine early warnings with pre-arranged financing in order to ensure fund release before the emergence of a crisis.
Accurate Medical Diagnoses
A doctor’s routine is a hectic one. Therefore, there is a chance that they overlook minute details, especially in the case of image-based test results. The doctors use traditional microscopic testing techniques to look for biomarkers in the body, which is a naturally occurring gene or characteristic that helps in the identification of a particular disease. Not only is this process time taking, but is also very expensive.
AI has solutions to all these problems. It increases the accuracy of the results factoring in the minute details. Additionally, the time and money spent on reaching a conclusive diagnosis are also reduced considerably with the use of automated diagnostic devices.
IBM Watson is well known for its discovery of cancer treatments. Recently made a major breakthrough in the disease Amyotrophic Lateral Sclerosis (ALS) in partnership with Barrow Neurological Institute. It was able to identify new genes linked to the disease after reviewing research pieces fed to it. Researchers know now what to target for therapy when they develop drugs for the treatment of ALS.
Last year, Google’s DeepMind trained a neural network to analyze 3D retinal scans and detect over 50 types of eye diseases with accuracy comparable to expert doctors. This will help doctors prioritize their patients and save the eyesight of the patients who are in need of immediate response.
If anything done in the name of progress is deteriorating the environment cannot be termed sustainable. It will only lead to poorer life quality for the majority population. Here, AI comes as a ray of hope in helping solve these global issues and making the world a better and more sustainable place to live.
If you are interested in knowing applications of various aspects of data science, and how they are helping us I suggest you read the following articles-
To summarize, in this article we discussed 5 of the pressing global issues that are plaguing our planet and how Ai is helping us curb these global issues. What do you think AI will achieve in the coming years? Do you think we missed any issues? Let us know what you think in the comment section below.
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